Some audio improving devices tend to modify audio signals, in either temporal domain or spectral domain, in order to improve overall quality of the audio and enhance users' experience correspondingly. Various audio improving devices have been developed for various purposes. Some typical examples of audio improving devices include:
Dialog Enhancer: Dialog is the most important component in a movie and radio or TV program to understand the story. Methods were developed to enhance the dialogs in order to increase their clarity and their intelligibility, especially for elders with decreasing hearing capability.
Surround Virtualizer: A surround virtualizer enables a surround (multi-channel) sound signal to be rendered over the internal speakers of the PC or over headphones. That is, with the stereo device (such as speakers and headphones), it creates virtually surround effect and provides cinematic experience for consumers.
Volume Leveler: A volume leveler aims at tuning the volume of the audio content on playback and keeping it almost consistent over the timeline based on a target loudness value.
Equalizer: An equalizer provides consistency of spectral balance, as known as “tone” or “timbre”, and allows users to configure the overall profile (curve or shape) of the frequency response (gain) on each individual frequency band, in order to emphasize certain sounds or remove undesired sounds. In a traditional equalizer, different equalizer presets may be provided for different sounds, such as different music genres. Once a preset is selected, or an equalization profile is set, the same equalization gains will be applied on the signal, until the equalization profile is modified manually. In contrast, a dynamic equalizer achieves the spectral balance consistency by continuously monitoring the spectral balance of the audio, comparing it to a desired tone, and dynamically adjusting an equalization filter to transform the audio's original tone into the desired tone.
In general, an audio improving devices has its own application scenario/context. That is, an audio improving device may be suitable for only a certain set of contents but not for all the possible audio signals, since different contents may need to be processed in different ways. For example, a dialog enhancement method is usually applied on movie content. If it is applied on music in which there are no dialogs, it may falsely boost some frequency sub-bands and introduce heavy timbre change and perceptual inconsistency. Similarly, if a noise suppression method is applied on music signals, strong artifacts will be audible.
However, for an audio processing system that usually comprises a set of audio improving devices, its input could be unavoidably all the possible types of audio signals. For example, an audio processing system, integrated in a PC, will receive audio content from a variety of sources, including movie, music, VoIP and game. Thus, identifying or differentiating the content being processed becomes important, in order to apply better algorithms or better parameters of each algorithm on the corresponding content.
In order to differentiate audio content and apply better parameters or better audio improving algorithms correspondingly, traditional systems usually pre-design a set of presets, and users are asked to choose a preset for the content being played. A preset usually encodes a set of audio improving algorithms and/or their best parameters that will be applied, such as a ‘Movie’ preset and a ‘Music’ preset which is specifically designed for movie or music playback.
However, manual selection is inconvenient for users. Users usually don't frequently switch among the predefined presets but just keep using one preset for all the content. In addition, even in some automatic solutions the parameters or algorithms setup in the presets are usually discrete (such as turn On or Off for a specific algorithm with respect to a specific content), it cannot adjust parameters in a content-based continuous manner.